메뉴 건너뛰기




Volumn , Issue , 2005, Pages

Optimal aggregation of classifiers and boosting maps in functional magnetic resonance imaging

Author keywords

[No Author keywords available]

Indexed keywords

MAGNETIC RESONANCE IMAGING; RISK PERCEPTION;

EID: 33744911694     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (11)
  • 2
    • 0041737619 scopus 로고    scopus 로고
    • Functional magnetic resonance imaging (FMRI) "brain reading, detecting and classifying distributed patterns of fmri activity in human visual cortex
    • Cox, D.D., Savoy, R.L. (2003) Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex, Neuroimage19, 2, 261-70.
    • (2003) Neuroimage19 , vol.2 , pp. 261-270
    • Cox, D.D.1    Savoy, R.L.2
  • 4
    • 1542367492 scopus 로고    scopus 로고
    • Convexity, classification, and risk bounds
    • U.C. Berkeley, Journal of the American Statistical Association.To appear
    • Bartlett, P. L., Jordan, M.I., McAuliffe, J. D. (2003) Convexity, classification, and risk bounds. Technical Report 638, Department of Statistics, U.C. Berkeley, 2003. Journal of the American Statistical Association.To appear.
    • (2003) Technical Report 638, Department of Statistics
    • Bartlett, P.L.1    Jordan, M.I.2    McAuliffe, J.D.3
  • 5
    • 0037274322 scopus 로고    scopus 로고
    • Bounding the generalization error of combined classifiers: Balancing the dimensionality and the margins
    • Koltchinskii, V., Panchenko, D. and Lozano, F. (2003) Bounding the generalization error of combined classifiers: balancing the dimensionality and the margins. A. Appl. Prob., 13, 1.
    • (2003) A. Appl. Prob. , vol.13 , pp. 1
    • Koltchinskii, V.1    Panchenko, D.2    Lozano, F.3
  • 6
    • 9444260333 scopus 로고    scopus 로고
    • Generalization bounds for voting classifiers based on sparsity and clustering
    • Eds.: M. Warmuth and B. Schoelkopf, Springer
    • Koltchinskii, V., Panchenko, D. and Andonova, S. (2003) Generalization bounds for voting classifiers based on sparsity and clustering. In: COLT2003, Lecture Notes in Artificial Intelligence, Eds.: M. Warmuth and B. Schoelkopf, Springer.
    • (2003) COLT2003, Lecture Notes in Artificial Intelligence
    • Koltchinskii, V.1    Panchenko, D.2    Andonova, S.3
  • 10
    • 0025773346 scopus 로고
    • Comparing functional (pet) images: The assessment of significant change
    • Friston, K., Frith, C., Liddle, P. and Frackowiak, R. (1991) Comparing functional (PET) images: The assessment of significant change. J. Cereb. Blood Flow Met.11, 690-699.
    • (1991) J. Cereb. Blood Flow Met. , vol.11 , pp. 690-699
    • Friston, K.1    Frith, C.2    Liddle, P.3    Frackowiak, R.4
  • 11
    • 24044435942 scopus 로고    scopus 로고
    • Reducing multiclass to binary: A unifying approach for margin classifiers
    • Allwein, E. L., Schapire, R. E., and Singer, Y. (2000) Reducing multiclass to binary: A unifying approach for margin classifiers. J. Machine Learning Research, 1, 113-141.
    • (2000) J. Machine Learning Research , vol.1 , pp. 113-141
    • Allwein, E.L.1    Schapire, R.E.2    Singer, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.